In a current computing cluster, an increasing quantity of applications of a hardware acceleration module has an increasingly higher requirement on performance of the hardware acceleration module. When a signal hardware acceleration module does not meet the requirement, more hardware acceleration modules may need to be installed. However, in a large cluster, hardware acceleration modules of different nodes have different load.
In an existing computer system, as processing amounts of various services increase, using only a central processing unit (CPU) to process services is increasingly unable to meet an application performance requirement. The CPU usually improves system processing performance by optimizing a software architecture, and this is difficult and limited in an improvement range. Currently, hardware performance improvement is a common system performance improvement manner in the industry. Some practical hardware accelerator engines are usually built in a data center server according to a service situation to assist a processor core to work, and running these engines does not consume a CPU resource. These hardware accelerator engines include but are not limited to an intelligent packet distribution engine, hardware encryption engine, hardware compression/decompression engine, graphics acceleration processing engine, and the like.
To avoid wasting hardware acceleration resources, the hardware acceleration resources or the hardware accelerator engines are usually distributed on different service nodes (for example, computer devices such as servers). However, when the hardware acceleration resources are shared or mutually called between multiple nodes, CPU and memory resources on the nodes usually need to be consumed for copying data, consequently causing occupation and consumption of the CPU and memory resources.